Anthropometrics, Cancer Risks, and Survival Outcomes in Adult Patients with Glioma – A Systematic Review and Meta-analysis

Anthropometrics, Cancer Risks, and Survival Outcomes in Adult Patients with Glioma – A Systematic Review and Meta-analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Anthropometrics, Cancer Risks, and Survival Outcomes in Adult Patients with Glioma – A Systematic Review and Meta-analysis Jaehyun Ahn, Joonseok Kim, Christopher Shin, Stephen Ahn This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5413962/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The association between anthropometric measures, including height and BMI, and cancer has been widely discussed, but their role glioma development and survival remains unclear due to conflicting evidence. We synthesized existing data on the relationship between these measures and both the incidence and survival outcomes of glioma patients. Methods Papers reporting relationship between anthropometric measures and the risk of glioma, both incidence and survival, were regarded as relevant. All relevant papers published until January 31, 2024, were selected from PubMed, EMBASE, and the Cochrane Library. Studies were evaluated according to the modified Newcastle Ottawa Scale. Results were reported following the PRISMA reporting guideline. Hazard ratios, relative risks, and 95% confidence intervals were pooled and synthesized. Findings Among 940 screened articles, 23 were included. Taller height was associated with increased glioma (HR per 10 cm, 1.19; CI, 1.16 to 1.23) and glioblastoma risk (HR per 10 cm, 1.25; CI, 1.18 to 1.31). Higher BMI correlated with an increased glioma risk, both in categorical (RR, 1.08; CI, 1.03 to 1.12) and continuous measures (HR per 5kg/m 2 , 1.01; CI, 1.00 to 1.03). Glioblastoma demonstrated a higher incidence (HR per 5kg/m 2 , 1.02; 95% CI 1.00 to 1.05) and improved survival (HR 0.75; 95% CI 0.59 to 0.96) with increasing BMI. Interpretation This study synthesizes current evidence to provide critical insights into the relationship between glioma and anthropometric measures. Gliomas were influenced by these measures in terms of incidence and survival. Further research is necessary to uncover the underlying mechanisms and develop preventative or therapeutic strategies. Glioma Anthropometric measurements Risk factors Survival Prognostic factor Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Anthropometric measures, including height and body mass index (BMI), have been well-established to be associated with the development and prognosis of various diseases such as cardiovascular diseases ( 1 ), particularly in relation to different types of cancers ( 2 , 3 ). Height was initially studied in breast cancer among women ( 4 ) and has since been explored in other cancers including kidney and colorectal cancer with consistent results ( 5 ). In addition, obesity, often measured using BMI and sometimes waist circumference, has also become a well-researched risk factor in various type of cancer including colorectal, liver, and prostate cancer ( 6 ). Interestingly, the concept of the "obesity paradox" has emerged, where obese cancer patients appear to have better survival outcomes ( 7 ). However, in the case of glioma—the most common primary brain tumour and the most aggressive form of brain cancer, with a median overall survival of less than five years ( 8 )—such studies are limited. Moreover, existing research presents conflicting results. For instance, five studies support the association between taller height and increased glioma risk ( 9 – 14 ), while three do not ( 15 – 17 ). Similarly, two studies demonstrate a significant relationship between BMI and glioma risk ( 15 , 18 ), whereas eleven report no significant association ( 10 – 12 , 14 , 16 , 17 , 19 – 24 ). Additionally, four studies highlight the presence of the obesity paradox ( 25 – 28 ), while one study refutes it ( 29 ). In this context, we aim to elucidate the potential associations between body height and BMI with the risk and survival of patients with adult-type diffuse gliomas, including glioblastoma. This study comprehensively assesses existing evidence regarding the relationship between body height or BMI and the occurrence or survival of patients diagnosed with these tumours. By synthesizing available data, we firstly seek to provide insights into these controversial issues in glioma patients, which could inform future research into the pathobiological mechanisms underlying glioma and help develop novel preventive or therapeutic strategies. Methods Search Strategy and Selection Criteria We followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline ( 30 ). A systematic search was conducted through three databases: PubMed, EMBASE, and the Cochrane Library. Articles published until January 31, 2024 were screened using the following search strategy: (‘Glioma’ OR ‘Glioblastoma’) AND (‘Body Mass Index’ OR ‘Obesity’ OR ‘Body Weight’ OR ‘Overweight’ OR ‘Body Height’) AND (‘Survival’ OR ‘Mortality’ OR ‘Death’ OR ‘Risk’ OR ‘Risk Factors’ OR ‘Proportional Hazards Models’) . Each of the MeSH terms above were connected with their synonyms using the Boolean operator OR . Only articles written in English were included. Retrospective and observational studies (i.e., cohort and case-control) that reported the association of anthropometric measures with the risk of glioma occurrence or death were selected. Screening was not restricted by study setting, size, race, or country but was limited to adult patients with glioma or glioblastoma. Studies missing either necessary outcomes or full text were also excluded. The study selection process was carried out in two stages, ensuring a rigorous approach. First, titles and abstracts were carefully screened; then, selected full-text articles were included based on the pre-defined selection criteria. This screening process was conducted by three independent authors (CS, JA, JK), with every article evaluated by at least two authors. Disagreements were resolved through discussion among three authors, including a third individual who did not perform the initial assessment. Although excluded from the final analysis, the reference lists of identified articles were manually searched. Data Collection and Quality Assessment Data were collected independently by using a predesigned spreadsheet. Collected items included authors, year of publication, study type, subject population, mean age, number of subjects, region, tumour type (glioma, glioblastoma, or both), timeframe for follow-up, cutoff of anthropometric measures, and outcomes (i.e., hazards ratio, relative risk, overall survival). The quality of every article was assessed based on modified Newcastle Ottawa Scale (NOS; range 1–9, with 1–3 indicating low quality, 4–6 indicating moderate quality, and 7–9 indicating high quality) ( 31 ). In both case-control and cohort studies, age was identified as the most important factor for comparability. A follow-up period of 5 years and a follow-up rate of 80% were deemed adequate. As the risk and survival of paediatric glioma patients are beyond the interest of this study, cohorts consisting of average adults were considered representative. Each study underwent assessment by two independent researchers. Disagreements were resolved through discussion among three researchers, including a third individual who did not perform the initial assessment. Statistical Analysis For the analysis of the relationship between categorical BMI and glioma risk, we sought to maximise inclusivity by employing relative risk (RR) as a measure of association. Studies reporting the number of events and total cases were utilized to compute risk ratios. For investigations into other relationships (continuous BMI and glioma risk, height and glioma risk, BMI and glioma survival) we exclusively considered studies reporting fully adjusted hazard ratios (HR). To standardise the discrepancy in set endpoints, we adopted the inverse value of reported hazard ratios from several studies. Pooled HRs, RRs, and their 95% confidence intervals (CIs) were determined using random-effects meta-analysis approach with generic inverse-variance method to integrate effect sizes from heterogeneous studies. For height, the effect of continuous increase of 10cm was analysed. The dichotomous difference at cutoff of 25kg/m 2 and continuous increase of 5kg/m 2 was analysed for BMI and tumour risk. Meanwhile, the relationship between survival and BMI was obtained at dichotomous comparison between high BMI versus low BMI due to discrepancies of BMI cutoff across studies. The degree of inconsistency across studies was evaluated using the I 2 statistic, with cutoff values of 25%, 50%, and 75% signifying low, moderate, and high heterogeneity, respectively. For the presence of substantial heterogeneity (I 2 > 50%), preference was given to the random-effects model. To explore potential sources of heterogeneity, we conducted predefined subgroup analyses based on sex, disease type (all-grade glioma, high-grade glioma, glioblastoma), and BMI cutoff. Subgroup differences were evaluated using the χ² test. Egger test and visually inspected funnel plots were used to assess the risk of publication bias. All statistical analyses were two-sided with significance level set at p-value < 0.05 and were performed using ‘R’ software version 4.0.3 (R Foundation for Statistical Computing, 2020). Results Initial systematic search yielded 940 articles, of which 30 (3.2%) met the inclusion criteria for detailed full-text review ( Fig. 1 ) . Among them, seven studies were excluded for one of the following reasons: unavailable outcome, unavailable number of subgroup patients, inappropriate timing of anthropometric measurement, and outdated definition of brain tumour (Supplementary Table S1 ) . Additionally, 18 studies identified via citation searching didn’t meet the inclusion criteria. Descriptive data for 23 studies included in our meta-analysis are listed in Table 1 . The mean NOS score was 7.13 (median, 7; range 5–9), indicating that the overall quality of the articles was high ( Table 2 ) . Table 1 Characteristics of Included Studies Authors Year Study type Subject Age (y, mean) Population (N) Region Tumor type Timeframe for follow-up Moseeva et al. ( 19 ) 2024 Retrospective cohort Mayak Production Association workers, exposed to radiation NA (NA) 22,377 Russia Glioma Start: 1964–1999 End: December 2018 Sang et al. ( 20 ) 2023 Retrospective cohort Adult diabetes patients enrolled in NHIS database NA (57.5) 1,893,057 South Korea Glioma Start: January 2009 End: December 2018 Shao et al. ( 21 ) 2022 Prospective cohort PLCO participants 42–78 (NA) 140,270 United States Glioma Start: 1993–2001 End: December 2009 Median follow-up: 12.04 years Ahn et al. ( 9 , 18 ) 2021 Retrospective cohort Adult patients enrolled in NHIS database 20–80 (51.3) 6,833,744 South Korea Glioma Start: January 2009 End: December 2017 Median follow-up: 7.3 years Cha et al. ( 25 ) 2021 Retrospective cohort Primary diagnosis of GBM at Seoul St. Mary’s Hospital 20–85 (61.0) 177 South Korea GBM Start: August 2008 End: December 2018 Mean follow-up: 19.2 months Valente Aguiar et al. ( 26 ) 2021 Retrospective cohort Primary diagnosis of GBM at CHUSJ NA (60 a ) 193 Portugal GBM Start: 2011 End: 2017 Median follow-up: 17.3 months Ogawa et al. ( 22 ) 2020 Prospective cohort JPHC participants 40–69 (51.8) 102,925 Japan Glioma Start: 1990, 1993 End: December 2012 Median follow-up: 18.1 years Bertoli et al. ( 23 ) 2018 Cross-sectional Case: primary diagnosis of HGG at clinical neuro-oncology unit of FINCB Control: propensity-matched random selection from ICANS database NA ( 50 ) Case: 51 Control: 51 Italy HGG Enrollment: March 2015-December 2015 Cote et al. ( 10 ) 2018 Prospective cohort Female nurse, Male health professionals 30–75 (46.4) 173,096 United States Glioma, GBM Start: 1976, 1986 End: June 2014, February 2015 Median follow-up: 34.2, 23.6 years Kabat et al. ( 24 ) 2018 Prospective cohort Post-menopausal women 50–79 (NA) 161,119 United States Glioma, GBM Start: 1993–1998 Median follow-up: 17.8 years Potharaju et al. ( 27 ) 2018 Retrospective cohort Primary diagnosis of GBM 18–82 (56.0 a ) 392 b India GBM Start: January 2008 End: June 2016 Median follow-up: 48.6 months Cata et al. ( 28 ) 2017 Retrospective cohort Primary diagnosis of GBM at M.D. Anderson Cancer Center NA (56.63) 381 United States GBM Start: January 2006 End: July 2015 He et al. ( 33 ) 2017 Retrospective cohort Primary diagnosis of HGG at SYSUCC 5–78 (45.0 a ) 331 China HGG Start: January 2001-July2014 End: October 2015 Wiedmann et al. ( 11 , 12 ) 2017 Prospective cohort Tuberculosis screening campaign participants 14–80 (43.4) 1,855,333 Norway Glioma, GBM Start: 1963–1975 End: December 2011 Little et al. ( 15 ) 2013 Case-control Primary diagnosis of glioma within 3 months 25–92 (55.5) Case: 1,111 Control: 1,096 United States Glioma Enrollment: December 2004-June 2012 Siegel et al. ( 34 ) 2013 Retrospective cohort Primary diagnosis of HGG within 3 months 25–92 ( 57 ) 853 United States HGG Start: February 2005-March 2012 Wiedmann et al. ( 16 ) 2013 Retrospective cohort HUNT participants 20–101 (47.5) 74,242 Norway Glioma Start: 1984–1986 End: December 2008 Median follow-up: 23.5 years Michaud et al. ( 17 ) 2011 Prospective cohort EPIC participants 35–70 (52.2) 380,775 Europe Glioma Start: 1991–2000 Mean follow-up: 8.4 years Jones et al. ( 29 ) 2010 Prospective cohort Primary diagnosis of GBM at UCSF, DUMC NA ( 58 ) 1,259 c United States GBM Start: January 1991–2008 Median follow-up: 40 months Moore et al. ( 13 ) 2009 Prospective cohort AARP members 50–71 ( 62 ) 499,437 United States Glioma Start: 1995–1996 End: December 2003 Benson et al. ( 14 ) 2008 Prospective cohort Middle-aged women 50–65 (55.9) 1,249,670 United Kingdom Glioma Start: May 1996-March 2001 End: December 2005 a median age b 249 out of 392 patients were included in the analysis c 60% of cases were included in the analysis AARP, American Association of Retired Persons; CHUSJ, Centro Hospitalar Universitário São João; EPIC, European Prospective Investigation into Cancer and Nutrition; FINCB, Foundation of the Carlo Besta Neurological Institute Milan; GBM, glioblastoma multiforme; HGG, high grade glioma; HUNT, The Nord–Trøndelag Health Study; ICANS, International Center for the Assessment of Nutrtional Status; JPHC, The Japan Public Health Center-Based Prospective Study; NHIS, Korean National Health Insurance System; PLCO, The Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; SYSUCC, Sun Yatsen University Cancer Center; Table 2 Quality Assessment for Included Studies Authors Year Selection Comparability Exposure/Outcome a Quality score c 1 2 3 4 1 2 3 Moseeva et al. ( 19 ) 2024 ☆ ★ ★ ☆ ★★ ★ ★ ★ 7 Sang et al. ( 20 ) 2023 ☆ ★ ★ ★ ★★ ★ ★ ★ 8 Shao et al. ( 21 ) 2022 ★ ★ ☆ ★ ★★ ☆ ★ ★ 7 Ahn et al. ( 18 ) 2021 ★ ★ ☆ ★ ★★ ★ ★ ★ 8 Ahn et al. ( 9 ) 2021 ★ ★ ★ ★ ★★ ★ ★ ★ 9 Cha et al. ( 25 ) 2021 ★ ★ ☆ ★ ★★ ★ ★ ★ 8 Valente Aguiar et al. ( 26 ) 2021 ★ ★ ★ ☆ ☆☆ ★ ★ ★ 6 Ogawa et al. ( 22 ) 2020 ★ ★ ☆ ☆ ★★ ★ ★ ★ 7 Bertoli et al. ( 23 ) 2018 ★ ★ ☆ ★ ★★ ★ ★ ☆ 7 Cote et al. ( 10 ) 2018 ☆ ★ ☆ ☆ ★☆ ★ ★ ★ 5 Kabat et al. ( 24 ) 2018 ☆ ★ ★ ★ ★★ ☆ ★ ☆ 6 Potharaju et al. ( 27 ) 2018 ★ ★ ★ ☆ ★★ ★ ☆ ★ 7 Cata et al. ( 28 ) 2017 ★ ★ ★ ☆ ★★ ★ ☆ ★ 7 He et al. ( 33 ) 2017 ★ ★ ★ ☆ ★★ ★ ☆ ☆ 6 Wiedmann et al. ( 11 , 12 ) 2017 ★ ★ ★ ★ ★★ ★ ★ ★ 9 Little et al. ( 15 ) 2013 ★ ★ ★ ★ ★★ ★ ★ ☆ 8 Siegel et al. ( 34 ) 2013 ★ ★ ★ ★ ★★ ☆ ★ ☆ 7 Wiedmann et al. ( 16 ) 2013 ★ ★ ★ ★ ★★ ★ ★ ★ 9 Michaud et al. ( 17 ) 2011 ★ ★ ☆ ★ ★★ ★ ★ ★ 8 Jones et al. ( 29 ) 2010 ★ ★ ☆ ☆ ★★ ★ ☆ ★ 6 Moore et al. ( 13 ) 2009 ☆ ★ ☆ ★ ★★ ★ ★ ☆ 6 Benson et al. ( 14 ) 2008 ☆ ★ ☆ ★ ★★ ★ ★ ★ 7 a assessed exposure for case-control studies and outcomes for cohort studies b applicable to cohort studies c assessed according to modified Newcastle Ottawa scale (range 1–9, a score of 1–3 indicates low quality, 4–6 indicates moderate quality, and 7–9 indicates high quality) NA, not applicable; Height and Risk of Glioma, Glioblastoma A total of eight studies reported data on height and glioma occurrence ( Supplementary Table S2 ) ( 9 – 17 ), with two of these studies specifically addressing the risk of glioblastoma ( 10 , 12 ). All studies indicated a positive association between height and the risk of both glioma (HR per 10cm, 1.19; 95% CI, 1.16–1.23; Fig. 2 a, 2 b) and glioblastoma (HR per 10cm, 1.25; 95% CI, 1.18–1.31; Fig. 3 a, 3 b). To clarify, the results from two papers were combined, as each analysis was conducted by the same research group using the same cohort ( 11 , 12 ). Given the well-established sex disparity in brain tumour incidence, particularly in meningioma ( 32 ), a subgroup analysis based on sex was further conducted. Five studies that stratified results by sex, along with one study that included only a female population, were selected for this analysis ( Supplementary Table S3 ) ( 10 – 15 ). Among patients with glioma, the effect size was greater in female patients (HR per 10cm, 1.24; 95% CI, 1.18–1.32) compared to male patients (HR per 10cm, 1.19; 95% CI, 1.14–1.25), as shown in Supplementary Figure S1 . BMI and Risk of Glioma, Glioblastoma We included a total of 13 studies examining the relationship between BMI and glioma risk ( Supplementary Table S4 ) ( 10 – 12 , 14 – 24 ). These studies investigated either the comparison of glioma risks across categorical BMI levels or the impact of every 5kg/m 2 increase in continuous BMI. Given the variability in BMI level cutoffs across studies, we opted to measure RRs for the analysis of categorical BMI and glioma risk. While previous research has yielded conflicting findings regarding the RR of BMI ≥ 25kg/m 2 compared to BMI < 25kg/m 2 , our pooled RR analysis demonstrated statistical significance (RR 1.08; 95% CI 1.03–1.12; Fig. 4 a, 4 b). Similarly, consistent results emerged in HRs for both glioma (HR 1.01; 95% CI 1.00-1.03; Fig. 5 a, 5 b) and glioblastoma (HR 1.02; 95% CI 1.00-1.05; Fig. 6 a, 6 b) risk with every 5kg/m 2 increase in continuous BMI. BMI and glioblastoma survival Among studies that investigated the impact of BMI on survival in glioblastoma or glioma patients, seven reported hazard ratios ( 25 – 29 , 33 , 34 ). The analysis included five studies focused on glioblastoma patients ( 25 – 29 ), with an additional two studies involving high-grade glioma patients included in sensitivity analysis ( 33 , 34 ). Detailed information and results from each study are summarized in Supplementary Table S5 . The pooled data revealed an association between higher BMI and improved survival outcomes in patients with glioblastoma (HR 0.75; 95% CI 0.59–0.96; Fig. 7 a). The Funnel plot showed asymmetry (Fig. 7 b). Sensitivity analysis indicated a nonsignificant relationship between higher BMI and survival outcomes in high grade glioma patients (HR 0.84; 95% CI 0.67–1.07; Supplementary Figure S2 ). Discussions Before our study, the relationship between height or BMI and glioma risk had been suggested, but the results were inconsistent, as shown in Supplementary Table S2 and S4 . To summarise, five studies have supported the association between height and glioma with HRs ranging from 1.16 to 1.31 ( 9 – 14 ), while three did not ( 15 – 17 ). Similarly, for BMI and glioma risk, two studies showed support with HRs ranging from 1.14 to 1.20 ( 15 , 18 ), while eleven found no significant association ( 10 – 12 , 14 , 16 , 17 , 19 – 24 ). Through our meta-analysis, we demonstrated a combined, statistically significant relationship. Specifically, for height, the pooled HR was 1.19 (95% CI: 1.16–1.23) for glioma risk, while for BMI, the HR was 1.08 (95% CI: 1.03–1.12), confirming a positive association between both height and BMI with glioma occurrence. Similar relationship was observed when analysing studies for glioma and glioblastoma risk per unit increase in BMI, with HRs of 1.01 (95% CI: 1.00–1.03) for glioma and 1.02 (95% CI: 1.00–1.05) for glioblastoma ( 10 – 12 , 15 – 17 ), thereby underscoring the importance of BMI as a modifiable risk factor for these tumours. To our knowledge, this is the first meta-analysis to synthesise these findings comprehensively. These results are further supported by consistent associations observed in various types of cancer ( 4 , 5 , 35 – 38 ). This meta-analysis also confirmed the association between higher BMI and improved survival outcomes in glioblastoma patients by synthesizing previously conflicting studies whose reported HR range from 0.56 to 1.09 ( 25 – 29 ). This phenomenon, often referred to as the “obesity paradox” because it contradicts the relationship observed in the general population ( 39 ), is seen in only a limited number of cancers ( 40 , 41 ). Nonetheless, in this analysis, we were able to validate the presence of the obesity paradox in glioblastoma patients, with an HR of 0.75 (95% CI: 0.59–0.96). The sensitivity analysis indicated a nonsignificant difference in survival between higher and lower BMI groups in combined high-grade glioma patients, in contrast to findings in glioblastoma, suggesting that the impact of BMI on survival may vary according to tumour grade. While biological mechanism behind each relationship is not yet fully understood, there are some studies that support our results. For the association between taller height and increased risk of glioma and glioblastoma, research on insulin-like growth factor (IGF) and related proteins (i.e., IGF receptors and IGF-binding proteins (IGFBPs)) provides a plausible explanation and offers hope for a novel target in cancer therapy ( 42 – 45 ). A number of in vitro and in vivo experiments supporting this hypothesis in glioblastoma have been published. High levels of IGF-related proteins have been found in glioblastoma ( 46 , 47 ), and tumour growth was inhibited when these proteins were targeted ( 48 – 53 ). More recently, efforts are being made to exploit the IGF system by particularly targeting IGFBP-2, which is gaining attention due to its presence in cancer cells and absence in normal mature brain cells ( 54 – 56 ). In our meta-analysis, we found that GBM was slightly more associated with tall stature than glioma, providing further support for the potential role of IGF-related proteins in gliomagenesis. One of proposed mechanisms for BMI and glioma risk is pro-inflammatory state associated with increased body weight, which may contribute to tumorigenesis. Elevated body mass and hyperglycaemia activate pro-inflammatory pathways via the receptor for advanced glycation end products (RAGE), potentially enhancing glioma growth by upregulating RAGE expression and suppressing antitumor immune responses ( 57 ). Another is genetic alterations related to higher BMI can lead to an increased development of malignancies. The fat mass and obesity-associated gene (FTO) is considered to be one of the key genetic contributors ( 58 , 59 ). For the obesity paradox observed in this study, various methodological and biological mechanisms have been proposed, including less aggressive tumour biology, better treatment response, and increased energy reserves ( 7 ). This biological perspective is supported by the association of sarcopenia with poor survival outcomes which has been observed in glioblastoma patients ( 60 ). Another possible explanation is that underweight patients, who tend to experience significantly worse outcomes compared to normal-weight individuals ( 34 ), may have skewed the analysis. Their inclusion in the lower BMI group could have exaggerated or falsely depicted the relationship between obesity and improved survival outcomes, potentially due to lower muscle mass ( 61 ). Our study has several limitations that warrant cautious interpretation. Only two studies are included in the analysis of height and glioblastoma risk ( 10 – 12 ), which is too small to draw a definitive conclusion. This limitation underscores the need for further research to confirm the relationship between height and glioblastoma. For the analysis of BMI and the risk of glioma occurrence, the BMI data in each study were not obtained at the same timeframe. Additionally, abdominal obesity, which interestingly has been shown to have a stronger association with glioma development, was beyond the scope of this analysis ( 18 ). Future research focusing on waist circumference may offer further insights. Significant heterogeneity among studies included in the analysis of BMI and glioblastoma survival is another concern. This may be partly attributed to variations in the definition of higher and lower BMI groups among studies, as well as differences in the inclusion or exclusion of underweight individuals in the lower BMI group ( 25 – 29 ). Differences in tumour biology also contribute to the observed heterogeneity, as demonstrated in a previous study ( 62 ). Additionally, the presence of possible publication bias, as suggested by the Funnel plot, highlights the need for cautious interpretation of these result. It is also noteworthy that two studies with conflicting findings were excluded from the analysis for not reporting hazard ratio, as summarised in Supplementary Table S6 ( 62 , 63 ). Therefore, further research is essential to better understand the true effect of BMI on survival outcomes. Conclusion Our meta-analysis offers valuable insights into the nuanced relationship between obesity and the risk or survivorship of glioma and glioblastoma. The findings confirm that taller height is associated with an increased risk of both glioma and glioblastoma, while higher BMI correlates with an elevated risk of glioma. Additionally, we observed a link between higher BMI and improved survival outcomes. However, larger, population-based studies are required to fully validate these associations. Additional research is also warranted to reveal precise biological mechanisms. Abbreviations BMI: body mass index CI: confidence interval FTO: fat mass and obesity-associated gene GBM: glioblastoma multiforme HR: hazard ratio IGF: insulin-like growth factor IGFBP: insulin-like growth factor binding protein MeSH: medical subject headings NOS: Newcastle Ottawa scale PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-analyses RAGE: receptor for advanced glycation end product RR: risk ratio Declarations Conflict of interest The authors have no conflict of interest to declare. Funding This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2024-00352668). This study was supported by Research Fund of Seoul St.Mary’s Hospital, The Catholic University of Korea. The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. Author Contribution J.A., J.K., S.A. wrote the main manuscript and prepared figures. S.A. conceptualized and designed the work. J.K. and S.A. revised the manuscript. All authors have approved the submitted version and agreed both to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature. Acknowledgment : None References Akin I, Nienaber CA. Obesity paradox in coronary artery disease. World J Cardiol. 2015;7(10):603–8. Santoni M, Cortellini A, Buti S. Unlocking the secret of the obesity paradox in renal tumours. Lancet Oncol. 2020;21(2):194–6. Sanchez A, Furberg H. Obesity Paradox in Patients With Non–Small Cell Lung Cancer Treated With Immunotherapy. JAMA Oncol. 2020;6(6):940–1. Albanes D, Jones DY, Schatzkin A, Micozzi MS, Taylor PR. 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Anthropometrics and Body Composition in Adults with High-Grade Gliomas: Effects of Disease-Related Variables. Nutr Cancer. 2018;70(3):431–40. Kabat GC, Rohan TE. Adiposity at different periods of life and risk of adult glioma in a cohort of postmenopausal women. Cancer Epidemiol. 2018;54:71–4. Cha JY, Park JS, Hong YK, Jeun SS, Ahn S. Impact of Body Mass Index on Survival Outcome in Patients with Newly Diagnosed Glioblastoma: A Retrospective Single-Center Study. Integr Cancer Ther. 2021;20. Valente Aguiar P, Carvalho B, Vaz R, Linhares P. Body mass index as an independent prognostic factor in glioblastoma. Cancer Causes Control. 2021;32(4):327–36. Potharaju M, Mangaleswaran B, Mathavan A, John R, Thamburaj V, Ghosh S, et al. Body Mass Index as a Prognostic Marker in Glioblastoma Multiforme: A Clinical Outcome. Int J Radiat Oncol Biol Phys. 2018;102(1):204–9. Cata JP, Hagan KB, Bhavsar SDO, Arunkumar R, Grasu R, Dang A, et al. The use of isoflurane and desflurane as inhalational agents for glioblastoma surgery. A survival analysis. J Clin Neurosci. 2017;35:82–7. Jones LW, Ali-Osman F, Lipp E, Marcello JE, McCarthy B, McCoy L, et al. Association between body mass index and mortality in patients with glioblastoma mutliforme. Cancer Causes Control. 2010;21(12):2195–201. Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. J Clin Epidemiol. 2009;62(10):e1–34. GA Wells BS, D O'Connell J, Peterson V, Welch M, Losos PT. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses Ottawa2011 [ https://www.ohri.ca/programs/clinical_epidemiology/oxford.asp Ostrom QT, Price M, Neff C, Cioffi G, Waite KA, Kruchko C, et al. CBTRUS Statistical Report: Primary Brain and Other Central Nervous System Tumors Diagnosed in the United States in 2016–2020. Neuro Oncol. 2023;25(12 Suppl 2):iv1–99. He ZQ, Ke C, Al-Nahari F, Duan H, Guo CC, Wang Y, et al. Low preoperative prognostic nutritional index predicts poor survival in patients with newly diagnosed high-grade gliomas. J Neurooncol. 2017;132(2):239–47. Siegel EM, Nabors LB, Thompson RC, Olson JJ, Browning JE, Madden MH, et al. Prediagnostic body weight and survival in high grade glioma. J Neurooncol. 2013;114(1):79–84. Choi YJ, Lee DH, Han K-D, Yoon H, Shin CM, Park YS, et al. Adult height in relation to risk of cancer in a cohort of 22,809,722 Korean adults. Br J Cancer. 2019;120(6):668–74. Renehan AG, Tyson M, Egger M, Heller RF, Zwahlen M. Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies. Lancet. 2008;371(9612):569–78. Gunnell D, Okasha M, Smith GD, Oliver SE, Sandhu J, Holly JM. Height, leg length, and cancer risk: a systematic review. Epidemiol Rev. 2001;23(2):313–42. Batty GD, Shipley MJ, Langenberg C, Marmot MG, Davey Smith G. Adult height in relation to mortality from 14 cancer sites in men in London (UK): evidence from the original Whitehall study. Ann Oncol. 2006;17(1):157–66. Di Angelantonio E, Bhupathiraju SN, Wormser D, Gao P, Kaptoge S, de Gonzalez AB, et al. Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet. 2016;388(10046):776–86. Petrelli F, Cortellini A, Indini A, Tomasello G, Ghidini M, Nigro O et al. Association of Obesity with Survival Outcomes in Patients with Cancer: A Systematic Review and Meta-analysis. JAMA Netw Open. 2021;4(3). Li Y, Li C, Wu G, Yang W, Wang X, Duan L, et al. The obesity paradox in patients with colorectal cancer: a systematic review and meta-analysis. Nutr Rev. 2022;80(7):1755–68. Clayton PE, Banerjee I, Murray PG, Renehan AG. Growth hormone, the insulin-like growth factor axis, insulin and cancer risk. Nat Rev Endocrinol. 2011;7(1):11–24. Morris JK, George LM, Wu T, Wald NJ. Insulin-like growth factors and cancer: no role in screening. Evidence from the BUPA study and meta-analysis of prospective epidemiological studies. Br J Cancer. 2006;95(1):112–7. Renehan AG, Zwahlen M, Minder C, O'Dwyer ST, Shalet SM, Egger M. Insulin-like growth factor (IGF)-I, IGF binding protein-3, and cancer risk: systematic review and meta-regression analysis. Lancet. 2004;363(9418):1346–53. Parra-Soto S, Ho FK, Pell JP, Celis-Morales C. Does insulin-like growth factor moderate the association between height and risk of cancer at 24 sites? Br J Cancer. 2020;123(11):1697–704. Friend KE, Khandwala HM, Flyvbjerg A, Hill H, Li J, McCutcheon IE. Growth hormone and insulin-like growth factor-I: effects on the growth of glioma cell lines. Growth Horm IGF Res. 2001;11(2):84–91. SCHLENSKA-LANGE A, KNÜPFER H, LANGE TJ, KIESS W. Cell Proliferation and Migration in Glioblastoma Multiforme Cell Lines are Influenced by Insulin-like Growth Factor I In Vitro. Anticancer Res. 2008;28(2A):1055–60. Zamykal M, Martens T, Matschke J, Günther HS, Kathagen A, Schulte A, et al. Inhibition of intracerebral glioblastoma growth by targeting the insulin-like growth factor 1 receptor involves different context-dependent mechanisms. Neuro Oncol. 2015;17(8):1076–85. Trojan J, Cloix JF, Ardourel MY, Chatel M, Anthony DD. Insulin-like growth factor type I biology and targeting in malignant gliomas. Neuroscience. 2007;145(3):795–811. Resnicoff M, Sell C, Rubini M, Coppola D, Ambrose D, Baserga R, et al. Rat Glioblastoma Cells Expressing an Antisense RNA to the Insulin-like Growth Factor-1 (IGF-1) Receptor Are Nontumorigenic and Induce Regression of Wild-Type Tumors1. Cancer Res. 1994;54(8):2218–22. Rininsland F, Johnson TR, Chernicky CL, Schulze E, Burfeind P, Ilan J et al. Suppression of insulin-like growth factor type I receptor by a triple-helix strategy inhibits IGF-I transcription and tumorigenic potential of rat C6 glioblastoma cells. Proceedings of the National Academy of Sciences. 1997;94(11):5854-9. Yin S, Girnita A, Strömberg T, Khan Z, Andersson S, Zheng H, et al. Targeting the insulin-like growth factor-1 receptor by picropodophyllin as a treatment option for glioblastoma. Neuro Oncol. 2010;12(1):19–27. D'Ambrosio C, Ferber A, Resnicoff M, Baserga R. A Soluble Insulin-like Growth Factor I Receptor That Induces Apoptosis of Tumor Cells in Vivo and Inhibits Tumorigenesis1. Cancer Res. 1996;56(17):4013–20. Li T, Forbes ME, Fuller GN, Li J, Yang X, Zhang W. IGFBP2: integrative hub of developmental and oncogenic signaling network. Oncogene. 2020;39(11):2243–57. Ben-Porath I, Thomson MW, Carey VJ, Ge R, Bell GW, Regev A, et al. An embryonic stem cell–like gene expression signature in poorly differentiated aggressive human tumors. Nat Genet. 2008;40(5):499–507. Fuller GN, Rhee CH, Hess KR, Caskey LS, Wang R, Bruner JM, et al. Reactivation of Insulin-like Growth Factor Binding Protein 2 Expression in Glioblastoma Multiforme: A Revelation by Parallel Gene Expression Profiling1. Cancer Res. 1999;59(17):4228–32. Zhang IY, Zhou H, Liu H, Zhang L, Gao H, Liu S, et al. Local and Systemic Immune Dysregulation Alters Glioma Growth in Hyperglycemic Mice. Clin Cancer Res. 2020;26(11):2740–53. Deng X, Su R, Stanford S, Chen J. Critical Enzymatic Functions of FTO in Obesity and Cancer. Front Endocrinol. 2018;9. Lan N, Lu Y, Zhang Y, Pu S, Xi H, Nie X et al. FTO – A Common Genetic Basis for Obesity and Cancer. Front Genet. 2020;11. Furtner J, Weller M, Weber M, Gorlia T, Nabors B, Reardon DA, et al. Temporal Muscle Thickness as a Prognostic Marker in Patients with Newly Diagnosed Glioblastoma: Translational Imaging Analysis of the CENTRIC EORTC 26071–22072 and CORE Trials. Clin Cancer Res. 2022;28(1):129–36. Guven DC, Aksun MS, Cakir IY, Kilickap S, Kertmen N. The association of BMI and sarcopenia with survival in patients with glioblastoma multiforme. Future Oncol. 2021;17(32):4405–13. Weller J, Schäfer N, Schaub C, Potthoff AL, Steinbach JP, Schlegel U, et al. Prognostic impact of obesity in newly-diagnosed glioblastoma: a secondary analysis of CeTeG/NOA-09 and GLARIUS. J Neurooncol. 2022;159(1):95–101. Schneider M, Potthoff AL, Scharnböck E, Heimann M, Schäfer N, Weller J, et al. Newly diagnosed glioblastoma in geriatric (65 +) patients: impact of patients frailty, comorbidity burden and obesity on overall survival. J Neurooncol. 2020;149(3):421–7. Supplementary Figures Supplementary Figures 1 and 2 are not available with this version. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5413962","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":376255631,"identity":"b21a44e1-7014-40a1-8cfe-67eecc2fdd64","order_by":0,"name":"Jaehyun Ahn","email":"","orcid":"","institution":"The Catholic University of Korea","correspondingAuthor":false,"prefix":"","firstName":"Jaehyun","middleName":"","lastName":"Ahn","suffix":""},{"id":376255632,"identity":"0a760042-c6fe-435f-8e17-0caed58633fb","order_by":1,"name":"Joonseok Kim","email":"","orcid":"","institution":"The Catholic University of Korea","correspondingAuthor":false,"prefix":"","firstName":"Joonseok","middleName":"","lastName":"Kim","suffix":""},{"id":376255633,"identity":"a976fbce-7113-4813-b4ec-5631cd577ae5","order_by":2,"name":"Christopher Shin","email":"","orcid":"","institution":"The Catholic University of Korea","correspondingAuthor":false,"prefix":"","firstName":"Christopher","middleName":"","lastName":"Shin","suffix":""},{"id":376255634,"identity":"86ad943a-0fbd-4792-9d1f-5f9a08797ad2","order_by":3,"name":"Stephen Ahn","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYNCCCiCWYGA8kADmsRFUz9jAcIaBgUeCgYEELYxtUC0MxGgx5z/+/HHhPDt5e+nmAwce1DDI8zewpX3Ap8VyRo5h88xtyYY9MscSDiQcYzCccYDt8Ax8Wgxu8DA28247wNgjkWNwILGBgXEDA3szXocZnD/+sJl3zgF7mBZ7wloOJBg28zYcSIRpSdzAwHYYv5YbOYazZxxLTu65kQbyi0TyjMNsyYQc9uBzQY2dbfuM5IMPf9TY2Pa3txnj1QICzEhsCVQuMVpGwSgYBaNgFGACAL0DSj7ERzBXAAAAAElFTkSuQmCC","orcid":"","institution":"The Catholic University of Korea","correspondingAuthor":true,"prefix":"","firstName":"Stephen","middleName":"","lastName":"Ahn","suffix":""}],"badges":[],"createdAt":"2024-11-08 06:08:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5413962/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5413962/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":71542119,"identity":"1e54191b-395e-4a40-92d7-1ac581490b87","added_by":"auto","created_at":"2024-12-16 14:40:42","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1651619,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA flow diagram\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5413962/v1/196ccc75ce902f98b7ca87a0.jpg"},{"id":71542620,"identity":"6865699a-0cb4-415d-9284-a39d7ed41689","added_by":"auto","created_at":"2024-12-16 14:48:42","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":251062,"visible":true,"origin":"","legend":"\u003cp\u003ea. Forest plot for height and glioma risk\u003c/p\u003e\n\u003cp\u003eb. Funnel plot for height and glioma risk\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5413962/v1/e92a77f5611db9089d497d38.jpg"},{"id":71542618,"identity":"1edacf73-d632-4dca-9548-0172f7d0e9a8","added_by":"auto","created_at":"2024-12-16 14:48:41","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":163983,"visible":true,"origin":"","legend":"\u003cp\u003ea. Forest plot for height and glioblastoma risk\u003c/p\u003e\n\u003cp\u003eb. Funnel plot for height and glioblastoma risk\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5413962/v1/acae6c80aa0aaa5ba1a6b974.jpg"},{"id":71542619,"identity":"3c5b3df9-6339-4bf1-bce7-87ac68cc0fa9","added_by":"auto","created_at":"2024-12-16 14:48:42","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":272695,"visible":true,"origin":"","legend":"\u003cp\u003ea. Forest plot for BMI (categorical) and glioma risk\u003c/p\u003e\n\u003cp\u003eb. Funnel plot for BMI (categorical) and glioma risk\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5413962/v1/29b694791057651e270918c3.jpg"},{"id":71544243,"identity":"682421e6-3a58-423b-9f0d-e90651c1b5cc","added_by":"auto","created_at":"2024-12-16 14:56:42","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":206761,"visible":true,"origin":"","legend":"\u003cp\u003ea. Forest plot for BMI (continuous) and glioma risk\u003c/p\u003e\n\u003cp\u003eb. Funnel plot for BMI (continuous) and glioma risk\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5413962/v1/e4b5231824ffaff424dce80e.jpg"},{"id":71544244,"identity":"15b21c34-efde-4be2-843a-e7497478970c","added_by":"auto","created_at":"2024-12-16 14:56:42","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":175127,"visible":true,"origin":"","legend":"\u003cp\u003ea. Forest plot for BMI (continuous) and glioblastoma risk\u003c/p\u003e\n\u003cp\u003eb. Funnel plot for BMI (continuous) and glioblastoma risk\u003c/p\u003e","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5413962/v1/3a2bef0944c03d287b66cff1.jpg"},{"id":71542127,"identity":"2d8f38e0-2b9e-4b7d-927f-7a1553d06735","added_by":"auto","created_at":"2024-12-16 14:40:42","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":218913,"visible":true,"origin":"","legend":"\u003cp\u003ea. Forest plot for BMI and glioblastoma survival\u003c/p\u003e\n\u003cp\u003eb. Funnel plot for BMI and glioblastoma survival\u003c/p\u003e","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5413962/v1/13ebb32d3e7d009e59803547.jpg"},{"id":71546497,"identity":"a8fe16f5-1285-4344-ba7f-e119a454ff6c","added_by":"auto","created_at":"2024-12-16 15:12:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3878926,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5413962/v1/d8d37eb1-9b62-411f-a35b-95d1981befd0.pdf"},{"id":71542617,"identity":"c3ca09d7-40d4-40a0-8a9c-606bcdb62e83","added_by":"auto","created_at":"2024-12-16 14:48:41","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":37273,"visible":true,"origin":"","legend":"","description":"","filename":"GBManthropometricSupplementaryTable240712CMplain.docx","url":"https://assets-eu.researchsquare.com/files/rs-5413962/v1/84c70ee7a13f92f87c19b52d.docx"},{"id":71542122,"identity":"8712c6b6-fece-4860-8996-bc839c3d7107","added_by":"auto","created_at":"2024-12-16 14:40:42","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":97261,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.png","url":"https://assets-eu.researchsquare.com/files/rs-5413962/v1/af8d17270238739437ab7b68.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Anthropometrics, Cancer Risks, and Survival Outcomes in Adult Patients with Glioma – A Systematic Review and Meta-analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAnthropometric measures, including height and body mass index (BMI), have been well-established to be associated with the development and prognosis of various diseases such as cardiovascular diseases (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e), particularly in relation to different types of cancers (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Height was initially studied in breast cancer among women (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) and has since been explored in other cancers including kidney and colorectal cancer with consistent results (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In addition, obesity, often measured using BMI and sometimes waist circumference, has also become a well-researched risk factor in various type of cancer including colorectal, liver, and prostate cancer (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Interestingly, the concept of the \"obesity paradox\" has emerged, where obese cancer patients appear to have better survival outcomes (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, in the case of glioma\u0026mdash;the most common primary brain tumour and the most aggressive form of brain cancer, with a median overall survival of less than five years (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u0026mdash;such studies are limited. Moreover, existing research presents conflicting results. For instance, five studies support the association between taller height and increased glioma risk (\u003cspan additionalcitationids=\"CR10 CR11 CR12 CR13\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), while three do not (\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Similarly, two studies demonstrate a significant relationship between BMI and glioma risk (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), whereas eleven report no significant association (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Additionally, four studies highlight the presence of the obesity paradox (\u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e), while one study refutes it (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn this context, we aim to elucidate the potential associations between body height and BMI with the risk and survival of patients with adult-type diffuse gliomas, including glioblastoma. This study comprehensively assesses existing evidence regarding the relationship between body height or BMI and the occurrence or survival of patients diagnosed with these tumours. By synthesizing available data, we firstly seek to provide insights into these controversial issues in glioma patients, which could inform future research into the pathobiological mechanisms underlying glioma and help develop novel preventive or therapeutic strategies.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSearch Strategy and Selection Criteria\u003c/h2\u003e \u003cp\u003eWe followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). A systematic search was conducted through three databases: PubMed, EMBASE, and the Cochrane Library. Articles published until January 31, 2024 were screened using the following search strategy: \u003cem\u003e(\u0026lsquo;Glioma\u0026rsquo; OR \u0026lsquo;Glioblastoma\u0026rsquo;) AND (\u0026lsquo;Body Mass Index\u0026rsquo; OR \u0026lsquo;Obesity\u0026rsquo; OR \u0026lsquo;Body Weight\u0026rsquo; OR \u0026lsquo;Overweight\u0026rsquo; OR \u0026lsquo;Body Height\u0026rsquo;) AND (\u0026lsquo;Survival\u0026rsquo; OR \u0026lsquo;Mortality\u0026rsquo; OR \u0026lsquo;Death\u0026rsquo; OR \u0026lsquo;Risk\u0026rsquo; OR \u0026lsquo;Risk Factors\u0026rsquo; OR \u0026lsquo;Proportional Hazards Models\u0026rsquo;)\u003c/em\u003e. Each of the MeSH terms above were connected with their synonyms using the Boolean operator \u003cem\u003eOR\u003c/em\u003e. Only articles written in English were included.\u003c/p\u003e \u003cp\u003eRetrospective and observational studies (i.e., cohort and case-control) that reported the association of anthropometric measures with the risk of glioma occurrence or death were selected. Screening was not restricted by study setting, size, race, or country but was limited to adult patients with glioma or glioblastoma. Studies missing either necessary outcomes or full text were also excluded.\u003c/p\u003e \u003cp\u003eThe study selection process was carried out in two stages, ensuring a rigorous approach. First, titles and abstracts were carefully screened; then, selected full-text articles were included based on the pre-defined selection criteria. This screening process was conducted by three independent authors (CS, JA, JK), with every article evaluated by at least two authors. Disagreements were resolved through discussion among three authors, including a third individual who did not perform the initial assessment. Although excluded from the final analysis, the reference lists of identified articles were manually searched.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Collection and Quality Assessment\u003c/h3\u003e\n\u003cp\u003eData were collected independently by using a predesigned spreadsheet. Collected items included authors, year of publication, study type, subject population, mean age, number of subjects, region, tumour type (glioma, glioblastoma, or both), timeframe for follow-up, cutoff of anthropometric measures, and outcomes (i.e., hazards ratio, relative risk, overall survival).\u003c/p\u003e \u003cp\u003eThe quality of every article was assessed based on modified Newcastle Ottawa Scale (NOS; range 1\u0026ndash;9, with 1\u0026ndash;3 indicating low quality, 4\u0026ndash;6 indicating moderate quality, and 7\u0026ndash;9 indicating high quality) (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In both case-control and cohort studies, age was identified as the most important factor for comparability. A follow-up period of 5 years and a follow-up rate of 80% were deemed adequate. As the risk and survival of paediatric glioma patients are beyond the interest of this study, cohorts consisting of average adults were considered representative. Each study underwent assessment by two independent researchers. Disagreements were resolved through discussion among three researchers, including a third individual who did not perform the initial assessment.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eFor the analysis of the relationship between categorical BMI and glioma risk, we sought to maximise inclusivity by employing relative risk (RR) as a measure of association. Studies reporting the number of events and total cases were utilized to compute risk ratios. For investigations into other relationships (continuous BMI and glioma risk, height and glioma risk, BMI and glioma survival) we exclusively considered studies reporting fully adjusted hazard ratios (HR). To standardise the discrepancy in set endpoints, we adopted the inverse value of reported hazard ratios from several studies. Pooled HRs, RRs, and their 95% confidence intervals (CIs) were determined using random-effects meta-analysis approach with generic inverse-variance method to integrate effect sizes from heterogeneous studies. For height, the effect of continuous increase of 10cm was analysed. The dichotomous difference at cutoff of 25kg/m\u003csup\u003e2\u003c/sup\u003e and continuous increase of 5kg/m\u003csup\u003e2\u003c/sup\u003e was analysed for BMI and tumour risk. Meanwhile, the relationship between survival and BMI was obtained at dichotomous comparison between high BMI versus low BMI due to discrepancies of BMI cutoff across studies. The degree of inconsistency across studies was evaluated using the I\u003csup\u003e2\u003c/sup\u003e statistic, with cutoff values of 25%, 50%, and 75% signifying low, moderate, and high heterogeneity, respectively. For the presence of substantial heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;50%), preference was given to the random-effects model. To explore potential sources of heterogeneity, we conducted predefined subgroup analyses based on sex, disease type (all-grade glioma, high-grade glioma, glioblastoma), and BMI cutoff. Subgroup differences were evaluated using the χ\u0026sup2; test. Egger test and visually inspected funnel plots were used to assess the risk of publication bias. All statistical analyses were two-sided with significance level set at p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 and were performed using \u0026lsquo;R\u0026rsquo; software version 4.0.3 (R Foundation for Statistical Computing, 2020).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eInitial systematic search yielded 940 articles, of which 30 (3.2%) met the inclusion criteria for detailed full-text review \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Among them, seven studies were excluded for one of the following reasons: unavailable outcome, unavailable number of subgroup patients, inappropriate timing of anthropometric measurement, and outdated definition of brain tumour \u003cb\u003e(Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003c/b\u003e. Additionally, 18 studies identified via citation searching didn\u0026rsquo;t meet the inclusion criteria. Descriptive data for 23 studies included in our meta-analysis are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The mean NOS score was 7.13 (median, 7; range 5\u0026ndash;9), indicating that the overall quality of the articles was high \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of Included Studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eStudy type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSubject\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAge (y, mean)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePopulation (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTumor type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTimeframe for follow-up\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoseeva et al. 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(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdult patients enrolled in NHIS database\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u0026ndash;80 (51.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,833,744\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGlioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: January 2009\u003c/p\u003e \u003cp\u003eEnd: December 2017\u003c/p\u003e \u003cp\u003eMedian follow-up: 7.3 years\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCha et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrimary diagnosis of GBM at Seoul St. Mary\u0026rsquo;s Hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u0026ndash;85 (61.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGBM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: August 2008\u003c/p\u003e \u003cp\u003eEnd: December 2018\u003c/p\u003e \u003cp\u003eMean follow-up: 19.2 months\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValente Aguiar et al. 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(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJPHC participants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u0026ndash;69 (51.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e102,925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eJapan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGlioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: 1990, 1993\u003c/p\u003e \u003cp\u003eEnd: December 2012\u003c/p\u003e \u003cp\u003eMedian follow-up: 18.1 years\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBertoli et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCase: primary diagnosis of HGG at clinical neuro-oncology unit of FINCB\u003c/p\u003e \u003cp\u003eControl: propensity-matched random selection from ICANS database\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCase: 51\u003c/p\u003e \u003cp\u003eControl: 51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eItaly\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEnrollment: March 2015-December 2015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCote et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFemale nurse,\u003c/p\u003e \u003cp\u003eMale health professionals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30\u0026ndash;75 (46.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e173,096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGlioma, GBM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: 1976, 1986\u003c/p\u003e \u003cp\u003eEnd: June 2014, February 2015\u003c/p\u003e \u003cp\u003eMedian follow-up: 34.2, 23.6 years\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKabat et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePost-menopausal women\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u0026ndash;79 (NA)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e161,119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGlioma, GBM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: 1993\u0026ndash;1998\u003c/p\u003e \u003cp\u003eMedian follow-up: 17.8 years\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotharaju et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrimary diagnosis of GBM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18\u0026ndash;82 (56.0 \u003csup\u003ea\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e392 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIndia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGBM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: January 2008\u003c/p\u003e \u003cp\u003eEnd: June 2016\u003c/p\u003e \u003cp\u003eMedian follow-up: 48.6 months\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCata et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrimary diagnosis of GBM at M.D. Anderson Cancer Center\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA (56.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGBM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: January 2006\u003c/p\u003e \u003cp\u003eEnd: July 2015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHe et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrimary diagnosis of HGG at SYSUCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u0026ndash;78 (45.0 \u003csup\u003ea\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: January 2001-July2014\u003c/p\u003e \u003cp\u003eEnd: October 2015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWiedmann et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTuberculosis\u003c/p\u003e \u003cp\u003escreening campaign participants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14\u0026ndash;80 (43.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,855,333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNorway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGlioma, GBM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: 1963\u0026ndash;1975\u003c/p\u003e \u003cp\u003eEnd: December 2011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLittle et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCase-control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrimary diagnosis\u003c/p\u003e \u003cp\u003eof glioma within 3 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u0026ndash;92 (55.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCase: 1,111\u003c/p\u003e \u003cp\u003eControl: 1,096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGlioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eEnrollment: December 2004-June 2012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiegel et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrimary diagnosis\u003c/p\u003e \u003cp\u003eof HGG within 3 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u0026ndash;92 (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: February 2005-March 2012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWiedmann et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRetrospective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHUNT participants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20\u0026ndash;101 (47.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74,242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNorway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGlioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: 1984\u0026ndash;1986\u003c/p\u003e \u003cp\u003eEnd: December 2008\u003c/p\u003e \u003cp\u003eMedian follow-up: 23.5 years\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMichaud et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEPIC participants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35\u0026ndash;70 (52.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e380,775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEurope\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGlioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: 1991\u0026ndash;2000\u003c/p\u003e \u003cp\u003eMean follow-up: 8.4 years\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJones et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePrimary diagnosis of GBM at UCSF, DUMC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,259 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGBM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: January 1991\u0026ndash;2008\u003c/p\u003e \u003cp\u003eMedian follow-up: 40 months\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoore et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAARP members\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u0026ndash;71 (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e499,437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGlioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: 1995\u0026ndash;1996\u003c/p\u003e \u003cp\u003eEnd: December 2003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenson et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProspective cohort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMiddle-aged women\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50\u0026ndash;65 (55.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,249,670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eUnited Kingdom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eGlioma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eStart: May 1996-March 2001\u003c/p\u003e \u003cp\u003eEnd: December 2005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003ea median age\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eb 249 out of 392 patients were included in the analysis\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003ec 60% of cases were included in the analysis\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eAARP, American Association of Retired Persons; CHUSJ, Centro Hospitalar Universit\u0026aacute;rio S\u0026atilde;o Jo\u0026atilde;o; EPIC, European Prospective Investigation into Cancer and Nutrition; FINCB, Foundation of the Carlo Besta Neurological Institute Milan; GBM, glioblastoma multiforme; HGG, high grade glioma; HUNT, The Nord\u0026ndash;Tr\u0026oslash;ndelag Health Study; ICANS, International Center for the Assessment of Nutrtional Status; JPHC, The Japan Public Health Center-Based Prospective Study; NHIS, Korean National Health Insurance System; PLCO, The Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; SYSUCC, Sun Yatsen University Cancer Center;\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eQuality Assessment for Included Studies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAuthors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e \u003cp\u003eSelection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eComparability\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eExposure/Outcome \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eQuality\u003c/p\u003e \u003cp\u003escore \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoseeva et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSang et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShao et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAhn et al. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAhn et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCha et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eValente Aguiar et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e☆☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOgawa et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBertoli et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCote et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKabat et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotharaju et al. (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCata et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHe et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWiedmann et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLittle et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiegel et al. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWiedmann et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMichaud et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJones et al. (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMoore et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenson et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e☆\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e★★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e★\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003ea assessed exposure for case-control studies and outcomes for cohort studies\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eb applicable to cohort studies\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003ec assessed according to modified Newcastle Ottawa scale (range 1\u0026ndash;9, a score of 1\u0026ndash;3 indicates low quality, 4\u0026ndash;6 indicates moderate quality, and 7\u0026ndash;9 indicates high quality)\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eNA, not applicable;\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eHeight and Risk of Glioma, Glioblastoma\u003c/h3\u003e\n\u003cp\u003eA total of eight studies reported data on height and glioma occurrence (\u003cb\u003eSupplementary Table S2\u003c/b\u003e) (\u003cspan additionalcitationids=\"CR10 CR11 CR12 CR13 CR14 CR15 CR16\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), with two of these studies specifically addressing the risk of glioblastoma (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). All studies indicated a positive association between height and the risk of both glioma (HR per 10cm, 1.19; 95% CI, 1.16\u0026ndash;1.23; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003ea, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003eb) and glioblastoma (HR per 10cm, 1.25; 95% CI, 1.18\u0026ndash;1.31; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003ea, \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). To clarify, the results from two papers were combined, as each analysis was conducted by the same research group using the same cohort (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Given the well-established sex disparity in brain tumour incidence, particularly in meningioma (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e), a subgroup analysis based on sex was further conducted. Five studies that stratified results by sex, along with one study that included only a female population, were selected for this analysis (\u003cb\u003eSupplementary Table S3\u003c/b\u003e) (\u003cspan additionalcitationids=\"CR11 CR12 CR13 CR14\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Among patients with glioma, the effect size was greater in female patients (HR per 10cm, 1.24; 95% CI, 1.18\u0026ndash;1.32) compared to male patients (HR per 10cm, 1.19; 95% CI, 1.14\u0026ndash;1.25), as shown in \u003cb\u003eSupplementary Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBMI and Risk of Glioma, Glioblastoma\u003c/h2\u003e \u003cp\u003eWe included a total of 13 studies examining the relationship between BMI and glioma risk (\u003cb\u003eSupplementary Table S4\u003c/b\u003e) (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). These studies investigated either the comparison of glioma risks across categorical BMI levels or the impact of every 5kg/m\u003csup\u003e2\u003c/sup\u003e increase in continuous BMI. Given the variability in BMI level cutoffs across studies, we opted to measure RRs for the analysis of categorical BMI and glioma risk. While previous research has yielded conflicting findings regarding the RR of BMI\u0026thinsp;\u0026ge;\u0026thinsp;25kg/m\u003csup\u003e2\u003c/sup\u003e compared to BMI\u0026thinsp;\u0026lt;\u0026thinsp;25kg/m\u003csup\u003e2\u003c/sup\u003e, our pooled RR analysis demonstrated statistical significance (RR 1.08; 95% CI 1.03\u0026ndash;1.12; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, \u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Similarly, consistent results emerged in HRs for both glioma (HR 1.01; 95% CI 1.00-1.03; Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e5\u003c/span\u003ea, \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e5\u003c/span\u003eb) and glioblastoma (HR 1.02; 95% CI 1.00-1.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003ea, \u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003eb) risk with every 5kg/m\u003csup\u003e2\u003c/sup\u003e increase in continuous BMI.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBMI and glioblastoma survival\u003c/h3\u003e\n\u003cp\u003eAmong studies that investigated the impact of BMI on survival in glioblastoma or glioma patients, seven reported hazard ratios (\u003cspan additionalcitationids=\"CR26 CR27 CR28\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). The analysis included five studies focused on glioblastoma patients (\u003cspan additionalcitationids=\"CR26 CR27 CR28\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), with an additional two studies involving high-grade glioma patients included in sensitivity analysis (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Detailed information and results from each study are summarized in \u003cb\u003eSupplementary Table S5\u003c/b\u003e.\u003c/p\u003e \u003cp\u003eThe pooled data revealed an association between higher BMI and improved survival outcomes in patients with glioblastoma (HR 0.75; 95% CI 0.59\u0026ndash;0.96; Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003ea). The Funnel plot showed asymmetry (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e7\u003c/span\u003eb). Sensitivity analysis indicated a nonsignificant relationship between higher BMI and survival outcomes in high grade glioma patients (HR 0.84; 95% CI 0.67\u0026ndash;1.07; \u003cb\u003eSupplementary Figure S2\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussions","content":"\u003cp\u003eBefore our study, the relationship between height or BMI and glioma risk had been suggested, but the results were inconsistent, as shown in \u003cb\u003eSupplementary Table S2\u003c/b\u003e and \u003cb\u003eS4\u003c/b\u003e. To summarise, five studies have supported the association between height and glioma with HRs ranging from 1.16 to 1.31 (\u003cspan additionalcitationids=\"CR10 CR11 CR12 CR13\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e), while three did not (\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Similarly, for BMI and glioma risk, two studies showed support with HRs ranging from 1.14 to 1.20 (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), while eleven found no significant association (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20 CR21 CR22 CR23\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Through our meta-analysis, we demonstrated a combined, statistically significant relationship. Specifically, for height, the pooled HR was 1.19 (95% CI: 1.16\u0026ndash;1.23) for glioma risk, while for BMI, the HR was 1.08 (95% CI: 1.03\u0026ndash;1.12), confirming a positive association between both height and BMI with glioma occurrence. Similar relationship was observed when analysing studies for glioma and glioblastoma risk per unit increase in BMI, with HRs of 1.01 (95% CI: 1.00\u0026ndash;1.03) for glioma and 1.02 (95% CI: 1.00\u0026ndash;1.05) for glioblastoma (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), thereby underscoring the importance of BMI as a modifiable risk factor for these tumours. To our knowledge, this is the first meta-analysis to synthesise these findings comprehensively. These results are further supported by consistent associations observed in various types of cancer (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan additionalcitationids=\"CR36 CR37\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis meta-analysis also confirmed the association between higher BMI and improved survival outcomes in glioblastoma patients by synthesizing previously conflicting studies whose reported HR range from 0.56 to 1.09 (\u003cspan additionalcitationids=\"CR26 CR27 CR28\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). This phenomenon, often referred to as the \u0026ldquo;obesity paradox\u0026rdquo; because it contradicts the relationship observed in the general population (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e), is seen in only a limited number of cancers (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). Nonetheless, in this analysis, we were able to validate the presence of the obesity paradox in glioblastoma patients, with an HR of 0.75 (95% CI: 0.59\u0026ndash;0.96). The sensitivity analysis indicated a nonsignificant difference in survival between higher and lower BMI groups in combined high-grade glioma patients, in contrast to findings in glioblastoma, suggesting that the impact of BMI on survival may vary according to tumour grade.\u003c/p\u003e \u003cp\u003eWhile biological mechanism behind each relationship is not yet fully understood, there are some studies that support our results. For the association between taller height and increased risk of glioma and glioblastoma, research on insulin-like growth factor (IGF) and related proteins (i.e., IGF receptors and IGF-binding proteins (IGFBPs)) provides a plausible explanation and offers hope for a novel target in cancer therapy (\u003cspan additionalcitationids=\"CR43 CR44\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). A number of \u003cem\u003ein vitro\u003c/em\u003e and \u003cem\u003ein vivo\u003c/em\u003e experiments supporting this hypothesis in glioblastoma have been published. High levels of IGF-related proteins have been found in glioblastoma (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e), and tumour growth was inhibited when these proteins were targeted (\u003cspan additionalcitationids=\"CR49 CR50 CR51 CR52\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e). More recently, efforts are being made to exploit the IGF system by particularly targeting IGFBP-2, which is gaining attention due to its presence in cancer cells and absence in normal mature brain cells (\u003cspan additionalcitationids=\"CR55\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). In our meta-analysis, we found that GBM was slightly more associated with tall stature than glioma, providing further support for the potential role of IGF-related proteins in gliomagenesis.\u003c/p\u003e \u003cp\u003eOne of proposed mechanisms for BMI and glioma risk is pro-inflammatory state associated with increased body weight, which may contribute to tumorigenesis. Elevated body mass and hyperglycaemia activate pro-inflammatory pathways via the receptor for advanced glycation end products (RAGE), potentially enhancing glioma growth by upregulating RAGE expression and suppressing antitumor immune responses (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Another is genetic alterations related to higher BMI can lead to an increased development of malignancies. The fat mass and obesity-associated gene (FTO) is considered to be one of the key genetic contributors (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor the obesity paradox observed in this study, various methodological and biological mechanisms have been proposed, including less aggressive tumour biology, better treatment response, and increased energy reserves (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). This biological perspective is supported by the association of sarcopenia with poor survival outcomes which has been observed in glioblastoma patients (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). Another possible explanation is that underweight patients, who tend to experience significantly worse outcomes compared to normal-weight individuals (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), may have skewed the analysis. Their inclusion in the lower BMI group could have exaggerated or falsely depicted the relationship between obesity and improved survival outcomes, potentially due to lower muscle mass (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur study has several limitations that warrant cautious interpretation. Only two studies are included in the analysis of height and glioblastoma risk (\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), which is too small to draw a definitive conclusion. This limitation underscores the need for further research to confirm the relationship between height and glioblastoma. For the analysis of BMI and the risk of glioma occurrence, the BMI data in each study were not obtained at the same timeframe. Additionally, abdominal obesity, which interestingly has been shown to have a stronger association with glioma development, was beyond the scope of this analysis (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Future research focusing on waist circumference may offer further insights. Significant heterogeneity among studies included in the analysis of BMI and glioblastoma survival is another concern. This may be partly attributed to variations in the definition of higher and lower BMI groups among studies, as well as differences in the inclusion or exclusion of underweight individuals in the lower BMI group (\u003cspan additionalcitationids=\"CR26 CR27 CR28\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Differences in tumour biology also contribute to the observed heterogeneity, as demonstrated in a previous study (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). Additionally, the presence of possible publication bias, as suggested by the Funnel plot, highlights the need for cautious interpretation of these result. It is also noteworthy that two studies with conflicting findings were excluded from the analysis for not reporting hazard ratio, as summarised in \u003cb\u003eSupplementary Table S6\u003c/b\u003e (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e). Therefore, further research is essential to better understand the true effect of BMI on survival outcomes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur meta-analysis offers valuable insights into the nuanced relationship between obesity and the risk or survivorship of glioma and glioblastoma. The findings confirm that taller height is associated with an increased risk of both glioma and glioblastoma, while higher BMI correlates with an elevated risk of glioma. Additionally, we observed a link between higher BMI and improved survival outcomes. However, larger, population-based studies are required to fully validate these associations. Additional research is also warranted to reveal precise biological mechanisms.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eBMI: body mass index\u003c/p\u003e\n\u003cp\u003eCI: confidence interval\u003c/p\u003e\n\u003cp\u003eFTO: fat mass and obesity-associated gene\u003c/p\u003e\n\u003cp\u003eGBM: glioblastoma multiforme\u003c/p\u003e\n\u003cp\u003eHR: hazard ratio\u003c/p\u003e\n\u003cp\u003eIGF: insulin-like growth factor\u003c/p\u003e\n\u003cp\u003eIGFBP: insulin-like growth factor binding protein\u003c/p\u003e\n\u003cp\u003eMeSH: medical subject headings\u003c/p\u003e\n\u003cp\u003eNOS: Newcastle Ottawa scale\u003c/p\u003e\n\u003cp\u003ePRISMA: Preferred Reporting Items for Systematic Reviews and Meta-analyses\u003c/p\u003e\n\u003cp\u003eRAGE: receptor for advanced glycation end product\u003c/p\u003e\n\u003cp\u003eRR: risk ratio\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eConflict of interest\u003c/h2\u003e \u003cp\u003eThe authors have no conflict of interest to declare.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2024-00352668). This study was supported by Research Fund of Seoul St.Mary\u0026rsquo;s Hospital, The Catholic University of Korea. The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJ.A., J.K., S.A. wrote the main manuscript and prepared figures. S.A. conceptualized and designed the work. J.K. and S.A. revised the manuscript. All authors have approved the submitted version and agreed both to be personally accountable for the author's own contributions and to ensure that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and the resolution documented in the literature.\u003c/p\u003e\u003ch2\u003eAcknowledgment\u003c/h2\u003e \u003cp\u003e: None\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAkin I, Nienaber CA. Obesity paradox in coronary artery disease. World J Cardiol. 2015;7(10):603\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSantoni M, Cortellini A, Buti S. Unlocking the secret of the obesity paradox in renal tumours. Lancet Oncol. 2020;21(2):194\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSanchez A, Furberg H. 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J Neurooncol. 2020;149(3):421\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Supplementary Figures","content":"\u003cp\u003eSupplementary Figures 1 and 2 are not available with this version.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Glioma, Anthropometric measurements, Risk factors, Survival, Prognostic factor","lastPublishedDoi":"10.21203/rs.3.rs-5413962/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5413962/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe association between anthropometric measures, including height and BMI, and cancer has been widely discussed, but their role glioma development and survival remains unclear due to conflicting evidence. We synthesized existing data on the relationship between these measures and both the incidence and survival outcomes of glioma patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePapers reporting relationship between anthropometric measures and the risk of glioma, both incidence and survival, were regarded as relevant. All relevant papers published until January 31, 2024, were selected from PubMed, EMBASE, and the Cochrane Library. Studies were evaluated according to the modified Newcastle Ottawa Scale. Results were reported following the PRISMA reporting guideline. Hazard ratios, relative risks, and 95% confidence intervals were pooled and synthesized.\u003c/p\u003e\u003ch2\u003eFindings\u003c/h2\u003e \u003cp\u003eAmong 940 screened articles, 23 were included. Taller height was associated with increased glioma (HR per 10 cm, 1.19; CI, 1.16 to 1.23) and glioblastoma risk (HR per 10 cm, 1.25; CI, 1.18 to 1.31). Higher BMI correlated with an increased glioma risk, both in categorical (RR, 1.08; CI, 1.03 to 1.12) and continuous measures (HR per 5kg/m\u003csup\u003e2\u003c/sup\u003e, 1.01; CI, 1.00 to 1.03). Glioblastoma demonstrated a higher incidence (HR per 5kg/m\u003csup\u003e2\u003c/sup\u003e, 1.02; 95% CI 1.00 to 1.05) and improved survival (HR 0.75; 95% CI 0.59 to 0.96) with increasing BMI.\u003c/p\u003e\u003ch2\u003eInterpretation\u003c/h2\u003e \u003cp\u003eThis study synthesizes current evidence to provide critical insights into the relationship between glioma and anthropometric measures. Gliomas were influenced by these measures in terms of incidence and survival. Further research is necessary to uncover the underlying mechanisms and develop preventative or therapeutic strategies.\u003c/p\u003e","manuscriptTitle":"Anthropometrics, Cancer Risks, and Survival Outcomes in Adult Patients with Glioma – A Systematic Review and Meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-16 14:40:37","doi":"10.21203/rs.3.rs-5413962/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b30f6ca2-a9b6-48e9-b58d-ca1bb2583640","owner":[],"postedDate":"December 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-16T14:48:39+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-16 14:40:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5413962","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5413962","identity":"rs-5413962","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}